DocumentCode
2491032
Title
Signal combination and classification scheme for neural networks
Author
Xu, Shenchu ; Dong, Jyang
Author_Institution
Dept. of Phys., Fujian Normal Univ., Fuzhou, China
Volume
2
fYear
1996
fDate
14-18 Oct 1996
Firstpage
1496
Abstract
The signal combinations are made as the stable attractors of the Hopfield (1982) model neural networks by using the methods of combinatorial optimization, then the classification scheme of binary numbers in the corresponding neural networks with a single-variance of the synaptic matrix elements is summarized and synthesized by the method which we borrowed from the Fu-Xi´s position on eight trigrams in I-ching (theory of changes)
Keywords
Hopfield neural nets; combinatorial mathematics; matrix algebra; optimisation; signal processing; Hopfield model neural networks; binary numbers classification; combinatorial optimization; neural networks; signal combinations; stable attractors; synaptic matrix elements; theory of changes; trigrams; Binary search trees; Circuit synthesis; Hopfield neural networks; Model driven engineering; Network synthesis; Neural networks; Neurons; Optimization methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 1996., 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-2912-0
Type
conf
DOI
10.1109/ICSIGP.1996.571158
Filename
571158
Link To Document